基于FAERS和JADER数据库的达格列净治疗心力衰竭不良事件挖掘OA

Objective:This study leverages pharmacovigilance data from the FDA Adverse Event Reporting System(FAERS)and the Japanese Adverse Drug Event Report(JADER)databases to identify and characterize potential adverse drug events(ADEs)associated with da-pagliflozin in patients with heart failure,thereby informing clinical risk assessment and safe prescribing practices.Methods:All dapagliflozin-related ADE reports submitted between Q1 2014 and Q1 2025 were retrieved from FAERS and JADER.Signal detection was performed using four complementary quantitative methods-Reporting Odds Ratio(ROR),the UK Medicines and Healthcare products Regulatory Agency(MH-RA)method,Bayesian Confidence Propagation Neural Network(BCPNN),and Multi-item Gamma Poisson Shrinker(MGPS).Results:A total of 2,162 dapagliflozin-associated ADE reports were identified(FAERS:n=1,805;JADER:n=357).Following multi-layered signal validation,81 preferred term(PT)signals were confirmed,spanning 15 System Organ Classes(SOCs).Infections and infestations constituted the largest SOC category,contributing 21 PTs(25.9%).Conclusions:In heart failure populations,dapagliflozin-associated ADEs are disproportionately represented in metabolic and nutritional disorders,infections and infestations,and general disorders and administration site conditions.The identifi-cation of several novel,label-unsupported high-strength signals-including osteomyelitis(not"osteitis"),polycythemia,phimosis,and systemic candidiasis-underscores the need for heightened clinical vigilance against these associated advers drug events in routine practice.